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The scalability of a computing system can be identified by at least three components: size, geographical distribution, and administrative constraints. Newer paradigms, such as clouds, grids, and clusters bring in more parameters to the aforementioned list, namely heterogeneity, energy consumption, and transparency. To optimize the performance of a computing system, it is manner that exploits heterogeneity and is scalable. Moreover, newer systems also demand energy efficiency as an integral part of schedulers. In this paper, the authors evaluate the behavior of low complexity energy-efficient algorithms for scheduling.
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